Import and process data

Learning

Model: Correct responses by age, trial, block number, and block condition

  correct_response_made
Predictors Odds Ratios CI
age scaled 1.2545 1.1664 – 1.3493
learning trial scaled 1.6632 1.6003 – 1.7286
reward condition1 1.6195 1.5376 – 1.7057
block number scaled 1.2588 1.1921 – 1.3293
age scaled × learning
trial scaled
1.1124 1.0703 – 1.1561
age scaled × reward
condition1
1.0722 1.0179 – 1.1294
learning trial scaled ×
reward condition1
1.1488 1.1150 – 1.1836
age scaled × block number
scaled
0.9780 0.9258 – 1.0331
learning trial scaled ×
block number scaled
1.0684 1.0356 – 1.1022
reward condition1 × block
number scaled
1.0580 1.0124 – 1.1057
age scaled × learning
trial scaled × reward
condition1
1.0462 1.0150 – 1.0784
(age scaled × learning
trial scaled) × block
number scaled
1.0065 0.9751 – 1.0389
(age scaled × reward
condition1) × block
number scaled
0.9897 0.9466 – 1.0347
(learning trial scaled ×
reward condition1) ×
block number scaled
1.0141 0.9845 – 1.0446
(age scaled × learning
trial scaled × reward
condition1) × block
number scaled
1.0075 0.9775 – 1.0383
Random Effects
σ2 3.29
τ00 subject_id 0.17
τ11 subject_id.re1.learning_trial_scaled 0.02
τ11 subject_id.re1.reward_condition1 0.07
τ11 subject_id.re1.block_number_scaled 0.08
τ11 subject_id.re1.learning_trial_scaled_by_reward_condition1 0.00
τ11 subject_id.re1.learning_trial_scaled_by_block_number_scaled 0.00
τ11 subject_id.re1.reward_condition1_by_block_number_scaled 0.04
τ11 subject_id.re1.learning_trial_scaled_by_reward_condition1_by_block_number_scaled 0.00
ρ01  
ρ01  
ICC 0.05
N subject_id 151
Observations 38352
Marginal R2 / Conditional R2 0.146 / 0.188

Figure 2A: Correct response by block condition, stimulus repetition, and age group

Supplementary Figure: Correct response by block condition and block number

Figure 2B: Generalization by block condition, category repetition, age group

Model: Correct response to first appearance of each stimulus

  correct_response_made
Predictors Odds Ratios CI
age scaled 1.0630 1.0168 – 1.1112
category rep scaled 1.2479 1.1926 – 1.3057
reward condition1 1.7160 1.6298 – 1.8068
block number scaled 1.0946 1.0478 – 1.1435
age scaled × category rep
scaled
1.0572 1.0101 – 1.1066
age scaled × reward
condition1
1.0705 1.0166 – 1.1272
category rep scaled ×
reward condition1
1.3200 1.2616 – 1.3812
age scaled × block number
scaled
1.0003 0.9572 – 1.0453
category rep scaled ×
block number scaled
1.0461 0.9999 – 1.0945
reward condition1 × block
number scaled
1.0953 1.0484 – 1.1443
age scaled × category rep
scaled × reward
condition1
1.0753 1.0273 – 1.1255
(age scaled × category
rep scaled) × block
number scaled
1.0225 0.9768 – 1.0704
(age scaled × reward
condition1) × block
number scaled
1.0027 0.9594 – 1.0479
(category rep scaled ×
reward condition1) ×
block number scaled
1.0678 1.0206 – 1.1171
(age scaled × category
rep scaled × reward
condition1) × block
number scaled
1.0283 0.9823 – 1.0764
Random Effects
σ2 3.29
τ00 subject_id 0.01
τ11 subject_id.re1.block_number_scaled 0.01
τ11 subject_id.re1.reward_condition1 0.03
τ11 subject_id.re1.block_number_scaled_by_reward_condition1 0.01
ρ01  
ρ01  
ICC 0.00
N subject_id 151
Observations 11267
Marginal R2 / Conditional R2 0.111 / 0.113

Supplementary Figure: Generalization by trial, reward condition, and block number

Figure 2C: WSLS by age group

Supplementary Figure: WSLS by block number

Supplementary Figure: WSLS by block number and age group

Model: Category win-stay lose-shift

  WSLS
Predictors Odds Ratios CI
age scaled 1.0283 0.9915 – 1.0665
learning trial scaled 1.0028 0.9798 – 1.0262
reward condition1 1.7550 1.6906 – 1.8218
block number scaled 1.0467 1.0147 – 1.0799
age scaled × learning
trial scaled
1.0084 0.9853 – 1.0321
age scaled × reward
condition1
1.0777 1.0382 – 1.1187
learning trial scaled ×
reward condition1
1.1690 1.1422 – 1.1963
age scaled × block number
scaled
0.9789 0.9489 – 1.0099
learning trial scaled ×
block number scaled
0.9845 0.9620 – 1.0076
reward condition1 × block
number scaled
1.0770 1.0523 – 1.1022
age scaled × learning
trial scaled × reward
condition1
1.0186 0.9952 – 1.0425
(age scaled × learning
trial scaled) × block
number scaled
1.0111 0.9879 – 1.0349
(age scaled × reward
condition1) × block
number scaled
0.9966 0.9737 – 1.0200
(learning trial scaled ×
reward condition1) ×
block number scaled
0.9908 0.9681 – 1.0141
(age scaled × learning
trial scaled × reward
condition1) × block
number scaled
0.9749 0.9525 – 0.9978
Random Effects
σ2 3.29
τ00 subject_id 0.03
τ11 subject_id.re1.reward_condition1 0.03
τ11 subject_id.re1.block_number_scaled 0.02
ρ01  
ρ01  
ICC 0.01
N subject_id 151
Observations 34390
Marginal R2 / Conditional R2 0.097 / 0.105

Stats: WSLS in first 10 trials

reward_condition mean_WSLS se_WSLS
Category-Predictive 0.6693 0.01003
Exemplar-Predictive 0.5899 0.01064

Supplementary Model: Influence of prior category and exemplar rewards on choice

  choice
Predictors Odds Ratios CI
prior cat reward scaled 1.8918 1.7996 – 1.9886
prior stim reward scaled 4.0021 3.5792 – 4.4750
reward condition1 0.9662 0.9324 – 1.0011
learning trial scaled 0.8433 0.8137 – 0.8740
age scaled 0.9354 0.8718 – 1.0037
prior cat reward scaled ×
reward condition1
1.5922 1.5218 – 1.6659
prior stim reward scaled
× reward condition1
1.1055 1.0358 – 1.1800
prior cat reward scaled ×
learning trial scaled
1.0757 1.0387 – 1.1140
prior stim reward scaled
× learning trial scaled
1.0595 1.0050 – 1.1169
reward condition1 ×
learning trial scaled
0.9712 0.9473 – 0.9957
prior cat reward scaled ×
age scaled
1.0388 0.9883 – 1.0918
prior stim reward scaled
× age scaled
1.3194 1.1807 – 1.4743
reward condition1 × age
scaled
0.9863 0.9517 – 1.0222
learning trial scaled ×
age scaled
0.9764 0.9420 – 1.0120
(prior cat reward scaled
× reward condition1) ×
learning trial scaled
1.1822 1.1388 – 1.2273
(prior stim reward scaled
× reward condition1) ×
learning trial scaled
0.8995 0.8564 – 0.9449
(prior cat reward scaled
× reward condition1) ×
age scaled
1.0558 1.0093 – 1.1045
(prior stim reward scaled
× reward condition1) ×
age scaled
1.0297 0.9643 – 1.0995
(prior cat reward scaled
× learning trial scaled)
× age scaled
1.0301 0.9944 – 1.0670
(prior stim reward scaled
× learning trial scaled)
× age scaled
0.9847 0.9335 – 1.0386
(reward condition1 ×
learning trial scaled) ×
age scaled
1.0006 0.9758 – 1.0260
(prior cat reward scaled
× reward condition1 ×
learning trial scaled) ×
age scaled
1.0441 1.0056 – 1.0842
(prior stim reward scaled
× reward condition1 ×
learning trial scaled) ×
age scaled
0.9644 0.9174 – 1.0138
Random Effects
σ2 3.29
τ00 subject_id 0.17
τ11 subject_id.re1.prior_cat_reward_scaled 0.05
τ11 subject_id.re1.prior_stim_reward_scaled 0.40
τ11 subject_id.re1.reward_condition1 0.03
τ11 subject_id.re1.learning_trial_scaled 0.03
τ11 subject_id.re1.prior_cat_reward_scaled_by_reward_condition1 0.03
τ11 subject_id.re1.prior_stim_reward_scaled_by_reward_condition1 0.09
τ11 subject_id.re1.prior_cat_reward_scaled_by_learning_trial_scaled 0.00
τ11 subject_id.re1.prior_stim_reward_scaled_by_learning_trial_scaled 0.02
τ11 subject_id.re1.reward_condition1_by_learning_trial_scaled 0.00
τ11 subject_id.re1.prior_cat_reward_scaled_by_reward_condition1_by_learning_trial_scaled 0.01
τ11 subject_id.re1.prior_stim_reward_scaled_by_reward_condition1_by_learning_trial_scaled 0.01
ρ01  
ρ01  
ICC 0.05
N subject_id 151
Observations 45702
Marginal R2 / Conditional R2 0.504 / 0.529

Supplementary Figure: Influence of prior category and exemplar rewards on choice

Memory

Overall descriptive memory stats

subject_id mean_mem se_mem
3718 0.8177 NA
3722 0.7917 NA
3768 0.75 NA
3770 0.6615 NA
3812 0.6702 NA
3816 0.776 NA
3817 0.6771 NA
3834 0.6667 NA
3835 0.7016 NA
3838 0.6878 NA
3841 0.776 NA
3844 0.7188 NA
3848 0.7407 NA
3853 0.7812 NA
3855 0.6562 NA
3856 0.7604 NA
3857 0.6979 NA
3861 0.8385 NA
3862 0.7135 NA
3871 0.5885 NA
3878 0.6875 NA
3883 0.776 NA
3898 0.7016 NA
3994 0.7604 NA
3998 0.8438 NA
3999 0.7083 NA
4003 0.724 NA
4007 0.6387 NA
4008 0.7812 NA
4011 0.8177 NA
4016 0.7812 NA
4022 0.7292 NA
4024 0.6719 NA
4028 0.6042 NA
4032 0.8385 NA
4036 0.6771 NA
4041 0.75 NA
4045 0.5885 NA
4050 0.7448 NA
4052 0.7552 NA
4062 0.7708 NA
4077 0.7083 NA
4087 0.6875 NA
4092 0.7135 NA
4097 0.5521 NA
4098 0.7708 NA
4284 0.7292 NA
4293 0.6875 NA
4294 0.7865 NA
4300 0.75 NA
4306 0.6823 NA
4487 0.6823 NA
4491 0.724 NA
4494 0.7865 NA
4495 0.8125 NA
4500 0.8281 NA
4506 0.8021 NA
4507 0.7448 NA
4508 0.8281 NA
4516 0.7031 NA
4521 0.7656 NA
4855 0.7487 NA
4857 0.7812 NA
5174 0.7135 NA
5175 0.625 NA
5178 0.7083 NA
5191 0.7604 NA
5193 0.776 NA
5433 0.7812 NA
5560 0.5604 NA
5565 0.7344 NA
5592 0.7865 NA
5626 0.7708 NA
5635 0.8281 NA
5639 0.6302 NA
5640 0.8542 NA
5641 0.8177 NA
5714 0.6667 NA
5719 0.6406 NA
5720 0.724 NA
5723 0.5104 NA
5757 0.7135 NA
5759 0.7344 NA
5809 0.7812 NA
5810 0.6094 NA
5811 0.776 NA
5813 0.6719 NA
5866 0.776 NA
5878 0.7344 NA
5884 0.7083 NA
5885 0.8542 NA
5887 0.7448 NA
5888 0.6283 NA
5889 0.8177 NA
5890 0.7656 NA
5938 0.6927 NA
6055 0.6302 NA
6130 0.6979 NA
6131 0.6719 NA
6132 0.7396 NA
6135 0.8542 NA
6153 0.6302 NA
6212 0.7031 NA
6217 0.7708 NA
6223 0.7448 NA
6256 0.6615 NA
6275 0.776 NA
6279 0.8333 NA
6280 0.8021 NA
6285 0.8115 NA
6286 0.6979 NA
6289 0.8125 NA
6292 0.7865 NA
6293 0.7188 NA
6294 0.7917 NA
6295 0.7344 NA
6380 0.6667 NA
6381 0.7016 NA
6407 0.6458 NA
6409 0.8281 NA
6410 0.7917 NA
6411 0.6458 NA
6414 0.7708 NA
6416 0.776 NA
6417 0.6615 NA
6460 0.651 NA
6461 0.6354 NA
6489 0.7812 NA
6490 0.849 NA
7056 0.7396 NA
7077 0.5521 NA
7083 0.6667 NA
7145 0.8177 NA
7147 0.6979 NA
7148 0.7292 NA
7196 0.8333 NA
7198 0.6387 NA
7199 0.7396 NA
7200 0.8281 NA
7240 0.6875 NA
7253 0.6354 NA
7579 0.4688 NA
7647 0.8542 NA
7653 0.7656 NA
7654 0.7292 NA
7695 0.5729 NA
7717 0.6771 NA
7731 0.8229 NA
7733 0.7917 NA
7909 0.6927 NA
8071 0.6406 NA
age_group mean_mem se_mem
Children 0.7122 0.01077
Adolescents 0.729 0.01024
Adults 0.741 0.01065

Memory delay stats

mean_delay sd_delay min_delay max_delay
7.132 1.3 6 10
memory_delay n
6 69
7 32
8 21
9 19
10 10

Supplementary Figure: AUC values by stimulus repetitions, block condition, age group

Model: AUC values by stimulus repetitions, block condition, age

  AUC
Predictors Estimates CI
age scaled 0.0147 0.0009 – 0.0285
reward condition1 -0.0091 -0.0135 – -0.0047
stim rep scaled 0.0432 0.0388 – 0.0475
age scaled × reward
condition1
-0.0042 -0.0086 – 0.0002
age scaled × stim rep
scaled
-0.0006 -0.0049 – 0.0038
reward condition1 × stim
rep scaled
0.0011 -0.0033 – 0.0055
(age scaled × reward
condition1) × stim rep
scaled
0.0023 -0.0021 – 0.0067
Random Effects
σ2 0.00
τ00 subject_id 0.01
ICC 0.60
N subject_id 151
Observations 912
Marginal R2 / Conditional R2 0.162 / 0.662

Figure 3A: AUC values by age group, memory specificity, block condition

foil_type mean_auc se_auc
category 0.8319 0.006013
exemplar 0.7118 0.005556

Model: AUCs by age, reward condition, memory specificity

  AUC
Predictors Estimates CI
age scaled 0.0159 0.0023 – 0.0294
reward condition1 -0.0084 -0.0132 – -0.0036
foil type1 0.0600 0.0552 – 0.0648
age scaled × reward
condition1
-0.0042 -0.0090 – 0.0006
age scaled × foil type1 0.0021 -0.0027 – 0.0069
reward condition1 × foil
type1
0.0013 -0.0035 – 0.0061
age scaled × reward
condition1 × foil type1
0.0016 -0.0032 – 0.0063
Random Effects
σ2 0.00
τ00 subject_id 0.01
ICC 0.63
N subject_id 151
Observations 608
Marginal R2 / Conditional R2 0.286 / 0.739

Model: AUCs by age, reward condition, foil type, memory delay

  AUC
Predictors Estimates CI
age scaled 0.0123 -0.0012 – 0.0258
reward condition1 -0.0083 -0.0131 – -0.0034
foil type1 0.0598 0.0549 – 0.0646
memory delay scaled -0.0148 -0.0281 – -0.0014
age scaled × reward
condition1
-0.0038 -0.0088 – 0.0011
age scaled × foil type1 0.0016 -0.0034 – 0.0065
reward condition1 × foil
type1
0.0014 -0.0034 – 0.0063
age scaled × memory delay
scaled
-0.0137 -0.0272 – -0.0002
reward condition1 ×
memory delay scaled
0.0021 -0.0028 – 0.0069
foil type1 × memory delay
scaled
-0.0026 -0.0075 – 0.0023
age scaled × reward
condition1 × foil type1
0.0019 -0.0030 – 0.0068
(age scaled × reward
condition1) × memory
delay scaled
0.0013 -0.0036 – 0.0063
(age scaled × foil type1)
× memory delay scaled
-0.0020 -0.0069 – 0.0030
(reward condition1 × foil
type1) × memory delay
scaled
-0.0001 -0.0050 – 0.0048
(age scaled × reward
condition1 × foil type1)
× memory delay scaled
0.0021 -0.0028 – 0.0070
Random Effects
σ2 0.00
τ00 subject_id 0.01
ICC 0.62
N subject_id 151
Observations 604
Marginal R2 / Conditional R2 0.312 / 0.738

Supplementary Figure: AUC values with delay

RL modeling

Choice weights

Figure: Choice weights histogram

Figure 2E: Choice weights boxplots

Presentation figure: Choice weights without age

Model: Choice weights by block condition and age

  est
Predictors Estimates CI
abstraction1 -0.4633 -0.5361 – -0.3905
reward condition1 0.2448 0.1720 – 0.3175
age scaled 0.1835 0.0839 – 0.2831
abstraction1 × reward
condition1
0.3241 0.2513 – 0.3969
abstraction1 × age scaled -0.0723 -0.1452 – 0.0005
reward condition1 × age
scaled
0.0542 -0.0186 – 0.1271
(abstraction1 × reward
condition1) × age scaled
0.0567 -0.0162 – 0.1295
Random Effects
σ2 0.83
τ00 subject_id 0.18
ICC 0.18
N subject_id 151
Observations 604
Marginal R2 / Conditional R2 0.296 / 0.422

Model: Exemplar choice weights across conditions

  est
Predictors Estimates CI
reward condition1 -0.0794 -0.1621 – 0.0034
Random Effects
σ2 0.53
τ00 subject_id 0.59
ICC 0.52
N subject_id 151
Observations 302
Marginal R2 / Conditional R2 0.006 / 0.526

Model: Category choice weights across conditions

  est
Predictors Estimates CI
reward condition1 0.5689 0.4688 – 0.6690
Random Effects
σ2 0.78
τ00 subject_id 0.20
ICC 0.20
N subject_id 151
Observations 302
Marginal R2 / Conditional R2 0.250 / 0.400

Supplementary Model: Relation between exemplar and category choice weights

  beta_e_scaled
Predictors Estimates CI
beta c scaled -0.0555 -0.1753 – 0.0643
age scaled 0.2633 0.1146 – 0.4120
block condition1 -0.0414 -0.1421 – 0.0594
beta c scaled × age
scaled
-0.0594 -0.1793 – 0.0605
beta c scaled × block
condition1
-0.1260 -0.2325 – -0.0195
age scaled × block
condition1
0.0458 -0.0568 – 0.1484
beta c scaled × age
scaled × block condition1
-0.0000 -0.1079 – 0.1078
Random Effects
σ2 0.46
τ00 subject_id 0.48
ICC 0.51
N subject_id 151
Observations 302
Marginal R2 / Conditional R2 0.076 / 0.548
## 
## Call:
## lm(formula = beta_e_scaled ~ beta_c_scaled * age_scaled, data = beta_ests_wide_exemp_pred)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.5077 -0.5259  0.0725  0.5729  2.8088 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)               2.019e-05  7.690e-02   0.000   0.9998    
## beta_c_scaled             1.469e-01  7.715e-02   1.904   0.0589 .  
## age_scaled                3.138e-01  7.730e-02   4.059 7.98e-05 ***
## beta_c_scaled:age_scaled -9.041e-02  7.599e-02  -1.190   0.2361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9449 on 147 degrees of freedom
## Multiple R-squared:  0.125,  Adjusted R-squared:  0.1072 
## F-statistic: 7.001 on 3 and 147 DF,  p-value: 0.0001961
  beta_e_scaled
Predictors Estimates CI
beta c scaled 0.1469 -0.0056 – 0.2994
age scaled 0.3138 0.1610 – 0.4665
beta c scaled × age
scaled
-0.0904 -0.2406 – 0.0598
Observations 151
R2 / R2 adjusted 0.125 / 0.107
## 
## Call:
## lm(formula = beta_e_scaled ~ beta_c_scaled * age_scaled, data = beta_ests_wide_cat_pred)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.77429 -0.64728  0.09172  0.69235  2.25603 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)   
## (Intercept)               0.01733    0.08263   0.210  0.83420   
## beta_c_scaled            -0.04539    0.08352  -0.543  0.58766   
## age_scaled                0.22259    0.08344   2.668  0.00849 **
## beta_c_scaled:age_scaled -0.07484    0.08586  -0.872  0.38482   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9855 on 147 degrees of freedom
## Multiple R-squared:  0.04813,    Adjusted R-squared:  0.0287 
## F-statistic: 2.477 on 3 and 147 DF,  p-value: 0.06364

Model: Relations between choice weights and points earned

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_c_c)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -279.190  -35.267    4.625   38.436  106.329 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  101.430      7.660  13.241  < 2e-16 ***
## est           38.762      4.837   8.013 2.99e-13 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 56.58 on 149 degrees of freedom
## Multiple R-squared:  0.3012, Adjusted R-squared:  0.2965 
## F-statistic: 64.21 on 1 and 149 DF,  p-value: 2.986e-13
  total_points
Predictors Estimates CI
est 38.7624 29.2036 – 48.3212
Observations 151
R2 / R2 adjusted 0.301 / 0.296
## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_e_c)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -267.742  -34.803    7.474   43.234  123.277 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   133.74       8.64  15.480   <2e-16 ***
## est            10.84       4.37   2.482   0.0142 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 66.33 on 149 degrees of freedom
## Multiple R-squared:  0.03969,    Adjusted R-squared:  0.03324 
## F-statistic: 6.158 on 1 and 149 DF,  p-value: 0.01419
  total_points
Predictors Estimates CI
est 10.8435 2.2090 – 19.4780
Observations 151
R2 / R2 adjusted 0.040 / 0.033
## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_c_e)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -324.49  -44.22    2.05   55.39  193.40 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  158.021      7.093   22.28   <2e-16 ***
## est           -6.648      6.924   -0.96    0.339    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 86.48 on 149 degrees of freedom
## Multiple R-squared:  0.006149,   Adjusted R-squared:  -0.0005209 
## F-statistic: 0.9219 on 1 and 149 DF,  p-value: 0.3385
  total_points
Predictors Estimates CI
est -6.6479 -20.3292 – 7.0335
Observations 151
R2 / R2 adjusted 0.006 / -0.001
## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_e_e)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -304.605  -36.510   -4.854   48.317  219.487 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   56.772     13.106   4.332 2.71e-05 ***
## est           58.972      6.908   8.537 1.47e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 71.08 on 149 degrees of freedom
## Multiple R-squared:  0.3285, Adjusted R-squared:  0.324 
## F-statistic: 72.88 on 1 and 149 DF,  p-value: 1.468e-14
  total_points
Predictors Estimates CI
est 58.9724 45.3227 – 72.6221
Observations 151
R2 / R2 adjusted 0.328 / 0.324

Figure 2D: Effect of choice weights on points earned

Relations between learning and memory

Model: Does the reward value of individual items relate to memory?

  mem_acc
Predictors Odds Ratios CI
age z 1.0752 0.9608 – 1.2033
reward condition1 0.9350 0.8881 – 0.9844
abs reward z 1.0180 0.9767 – 1.0610
reward sign1 0.9407 0.9000 – 0.9832
age z × reward condition1 0.9486 0.9011 – 0.9986
age z × abs reward z 0.9997 0.9594 – 1.0416
reward condition1 × abs
reward z
0.9412 0.9031 – 0.9810
age z × reward sign1 0.9914 0.9486 – 1.0361
reward condition1 ×
reward sign1
0.9945 0.9549 – 1.0357
abs reward z × reward
sign1
0.9861 0.9461 – 1.0279
(age z × reward
condition1) × abs reward
z
0.9358 0.8981 – 0.9751
age z × reward condition1
× reward sign1
0.9933 0.9539 – 1.0344
age z × abs reward z ×
reward sign1
1.0146 0.9736 – 1.0572
reward condition1 × abs
reward z × reward sign1
0.9755 0.9358 – 1.0168
age z × reward condition1
× abs reward z × reward
sign1
1.0175 0.9765 – 1.0603
Random Effects
σ2 3.29
τ00 subject_id 0.43
τ11 subject_id.re1.reward_condition1 0.04
τ11 subject_id.re1.reward_sign1 0.01
ρ01  
ρ01  
ICC 0.12
N subject_id 151
Observations 13669
Marginal R2 / Conditional R2 0.008 / 0.122

Do points earned during learning relate to memory?

Model: AUC by points earned

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: AUC ~ age_scaled * points_scaled * abstraction * reward_condition +  
##     (1 | subject_id)
##    Data: data
## 
## REML criterion at convergence: -1249
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.4573 -0.5178  0.0325  0.6283  2.5841 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  subject_id (Intercept) 0.005858 0.07654 
##  Residual               0.003619 0.06016 
## Number of obs: 608, groups:  subject_id, 151
## 
## Fixed effects:
##                                                           Estimate Std. Error
## (Intercept)                                              7.710e-01  6.843e-03
## age_scaled                                               1.277e-02  6.865e-03
## points_scaled                                            8.960e-03  4.357e-03
## abstraction1                                             6.032e-02  2.607e-03
## reward_condition1                                       -6.419e-03  2.675e-03
## age_scaled:points_scaled                                -3.026e-04  4.321e-03
## age_scaled:abstraction1                                  4.972e-04  2.655e-03
## points_scaled:abstraction1                               5.044e-03  2.941e-03
## age_scaled:reward_condition1                            -2.624e-03  2.755e-03
## points_scaled:reward_condition1                         -3.825e-03  3.593e-03
## abstraction1:reward_condition1                          -1.082e-04  2.607e-03
## age_scaled:points_scaled:abstraction1                    1.693e-04  2.780e-03
## age_scaled:points_scaled:reward_condition1              -4.781e-03  3.312e-03
## age_scaled:abstraction1:reward_condition1               -9.863e-04  2.655e-03
## points_scaled:abstraction1:reward_condition1             6.957e-03  2.941e-03
## age_scaled:points_scaled:abstraction1:reward_condition1  4.803e-03  2.780e-03
##                                                                 df t value
## (Intercept)                                              1.532e+02 112.665
## age_scaled                                               1.554e+02   1.859
## points_scaled                                            5.791e+02   2.057
## abstraction1                                             4.379e+02  23.134
## reward_condition1                                        4.485e+02  -2.400
## age_scaled:points_scaled                                 5.898e+02  -0.070
## age_scaled:abstraction1                                  4.379e+02   0.187
## points_scaled:abstraction1                               4.379e+02   1.715
## age_scaled:reward_condition1                             4.531e+02  -0.953
## points_scaled:reward_condition1                          5.070e+02  -1.065
## abstraction1:reward_condition1                           4.379e+02  -0.041
## age_scaled:points_scaled:abstraction1                    4.379e+02   0.061
## age_scaled:points_scaled:reward_condition1               4.987e+02  -1.443
## age_scaled:abstraction1:reward_condition1                4.379e+02  -0.372
## points_scaled:abstraction1:reward_condition1             4.379e+02   2.366
## age_scaled:points_scaled:abstraction1:reward_condition1  4.379e+02   1.728
##                                                         Pr(>|t|)    
## (Intercept)                                               <2e-16 ***
## age_scaled                                                0.0649 .  
## points_scaled                                             0.0402 *  
## abstraction1                                              <2e-16 ***
## reward_condition1                                         0.0168 *  
## age_scaled:points_scaled                                  0.9442    
## age_scaled:abstraction1                                   0.8515    
## points_scaled:abstraction1                                0.0870 .  
## age_scaled:reward_condition1                              0.3413    
## points_scaled:reward_condition1                           0.2876    
## abstraction1:reward_condition1                            0.9669    
## age_scaled:points_scaled:abstraction1                     0.9515    
## age_scaled:points_scaled:reward_condition1                0.1496    
## age_scaled:abstraction1:reward_condition1                 0.7104    
## points_scaled:abstraction1:reward_condition1              0.0184 *  
## age_scaled:points_scaled:abstraction1:reward_condition1   0.0848 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  AUC
Predictors Estimates CI
age scaled 0.0128 -0.0007 – 0.0262
points scaled 0.0090 0.0004 – 0.0175
abstraction1 0.0603 0.0552 – 0.0654
reward condition1 -0.0064 -0.0117 – -0.0012
age scaled × points
scaled
-0.0003 -0.0088 – 0.0082
age scaled × abstraction1 0.0005 -0.0047 – 0.0057
points scaled ×
abstraction1
0.0050 -0.0007 – 0.0108
age scaled × reward
condition1
-0.0026 -0.0080 – 0.0028
points scaled × reward
condition1
-0.0038 -0.0109 – 0.0032
abstraction1 × reward
condition1
-0.0001 -0.0052 – 0.0050
age scaled × points
scaled × abstraction1
0.0002 -0.0053 – 0.0056
age scaled × points
scaled × reward
condition1
-0.0048 -0.0113 – 0.0017
age scaled × abstraction1
× reward condition1
-0.0010 -0.0062 – 0.0042
points scaled ×
abstraction1 × reward
condition1
0.0070 0.0012 – 0.0127
age scaled × points
scaled × abstraction1 ×
reward condition1
0.0048 -0.0007 – 0.0103
Random Effects
σ2 0.00
τ00 subject_id 0.01
ICC 0.62
N subject_id 151
Observations 608
Marginal R2 / Conditional R2 0.303 / 0.734

Figure 3B: AUC by performance group and reward condition

Do choice weights relate to memory?

Model: AUC by age, exemplar choice weights, specificity, block condition

  AUC
Predictors Estimates CI
age scaled 0.0097 -0.0036 – 0.0230
beta scaled 0.0180 0.0087 – 0.0273
abstraction1 0.0610 0.0560 – 0.0659
reward condition1 -0.0052 -0.0103 – -0.0002
age scaled × beta scaled 0.0159 0.0051 – 0.0267
age scaled × abstraction1 0.0038 -0.0012 – 0.0088
beta scaled ×
abstraction1
-0.0044 -0.0098 – 0.0009
age scaled × reward
condition1
-0.0003 -0.0054 – 0.0048
beta scaled × reward
condition1
-0.0097 -0.0158 – -0.0035
abstraction1 × reward
condition1
-0.0001 -0.0051 – 0.0048
age scaled × beta scaled
× abstraction1
-0.0041 -0.0099 – 0.0018
age scaled × beta scaled
× reward condition1
-0.0075 -0.0141 – -0.0009
age scaled × abstraction1
× reward condition1
0.0011 -0.0039 – 0.0061
beta scaled ×
abstraction1 × reward
condition1
-0.0006 -0.0059 – 0.0048
age scaled × beta scaled
× abstraction1 × reward
condition1
0.0044 -0.0014 – 0.0102
Random Effects
σ2 0.00
τ00 subject_id 0.01
ICC 0.62
N subject_id 151
Observations 608
Marginal R2 / Conditional R2 0.322 / 0.741

Figure 3C: AUC by exemplar choice weights - model effects

Model: AUC by age, category choice weights, specificity, block condition

  AUC
Predictors Estimates CI
age scaled 0.0196 0.0054 – 0.0337
beta scaled 0.0000 -0.0083 – 0.0084
abstraction1 0.0593 0.0536 – 0.0649
reward condition1 -0.0076 -0.0142 – -0.0010
age scaled × beta scaled -0.0017 -0.0101 – 0.0066
age scaled × abstraction1 0.0025 -0.0033 – 0.0082
beta scaled ×
abstraction1
0.0070 0.0014 – 0.0126
age scaled × reward
condition1
-0.0029 -0.0096 – 0.0039
beta scaled × reward
condition1
0.0001 -0.0069 – 0.0071
abstraction1 × reward
condition1
-0.0019 -0.0075 – 0.0038
age scaled × beta scaled
× abstraction1
-0.0012 -0.0069 – 0.0045
age scaled × beta scaled
× reward condition1
-0.0070 -0.0141 – 0.0001
age scaled × abstraction1
× reward condition1
0.0014 -0.0043 – 0.0072
beta scaled ×
abstraction1 × reward
condition1
0.0022 -0.0035 – 0.0078
age scaled × beta scaled
× abstraction1 × reward
condition1
-0.0023 -0.0080 – 0.0034
Random Effects
σ2 0.00
τ00 subject_id 0.01
ICC 0.64
N subject_id 151
Observations 608
Marginal R2 / Conditional R2 0.290 / 0.741

Figure 3C: AUC by category choice weights: model effects

Figure (for presentation): Category and exemplar memory by exemplar choice weights

Figure (for presentation): Category and exemplar memory by category choice weights

Relations between age and other model parameters

Model: Initial Q values by age

  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.7336 0.09476 7.742 1.38e-12
age_scaled -0.2009 0.09508 -2.113 0.03625
Fitting linear model: q_init ~ age_scaled
Observations Residual Std. Error \(R^2\) Adjusted \(R^2\)
151 1.164 0.0291 0.02258
  q_init
Predictors Estimates CI
age scaled -0.2009 -0.3888 – -0.0130
Observations 151
R2 / R2 adjusted 0.029 / 0.023

Supplementary Figure: Initial Q values by age

Model: Alpha values by age

  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.6771 0.07922 -8.547 1.39e-14
age_scaled 0.007934 0.07949 0.09982 0.9206
Fitting linear model: alpha ~ age_scaled
Observations Residual Std. Error \(R^2\) Adjusted \(R^2\)
151 0.9735 6.686e-05 -0.006644
  alpha
Predictors Estimates CI
age scaled 0.0079 -0.1491 – 0.1650
Observations 151
R2 / R2 adjusted 0.000 / -0.007